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At least 973 records · Page 54

MO-G-BRE-05: Clinical Process Improvement and Billing in Radiation Oncology: A Case Study of Applying FMEA for CPT Code 77336 (continuing Medical Physics Consultation)

Purpose: The improvement of quality in healthcare can be assessed by Failure Mode and Effects Analysis (FMEA). In radiation oncology, FMEA, as applied to the billing CPT code 77336, can improve both charge capture and, most importantly, quality of the performed services. Methods: We created an FMEA table for the process performed under CPT code 77336. For a given process step, each member of the assembled team (physicist, dosimetrist, and therapist) independently assigned numerical values for: probability of occurrence (O, 1–10), severity (S, 1–10), and probability of detection (D, 1–10) for every failure mode cause and effect combination. The risk priority number, RPN, was then calculated as a product of O, S and D from which an average RPN was calculated for each combination mentioned above. A fault tree diagram, with each process sorted into 6 categories, was created with linked RPN. For processes with high RPN recommended actions were assigned. 2 separate R and V systems (Lantis and EMR-based ARIA) were considered. Results: We identified 9 potential failure modes and corresponding 19 potential causes of these failure modes all resulting in unjustified 77336 charge and compromised quality of care. In Lantis, the range of RPN was 24.5–110.8, and of S values – 2–10. The highest ranking RPN of 110.8 came from the failure mode described as “end-of-treatment check not done before the completion of treatment”, and the highest S value of 10 (RPN=105) from “overrides not checked”. For the same failure modes, within ARIA electronic environment with its additional controls, RPN values were significantly lower (44.3 for end-of-treatment missing check and 20.0 for overrides not checked). Conclusion: Our work has shown that when charge capture was missed that also resulted in some services not being performed. Absence of such necessary services may result in sub-optimal quality of care rendered to patients.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

SU-D-303-03: Impact of Uncertainty in T1 Measurements On Quantification of Dynamic Contrast Enhanced MRI

Purpose: Quantification of dynamic contrast enhanced (DCE) MRI requires native longitudinal relaxation time (T1) measurement. This study aimed to assess uncertainty in T1 measurements using two different methods. Methods and Materials: Brain MRI scans were performed on a 3T scanner in 9 patients who had low grade/benign tumors and partial brain radiotherapy without chemotherapy at pre-RT, week-3 during RT (wk-3), end-RT, and 1, 6 and 18 months after RT. T1-weighted images were acquired using gradient echo sequences with 1) 2 different flip angles (50 and 150), and 2) 5 variable TRs (100–2000ms). After creating quantitative T1 maps, average T1 was calculated in regions of interest (ROI), which were distant from tumors and received a total of accumulated radiation doses < 5 Gy at wk-3. ROIs included left and right normal Putamen and Thalamus (gray matter: GM), and frontal and parietal white matter (WM). Since there were no significant or even a trend of T1 changes from pre-RT to wk-3 in these ROIs, a relative repeatability coefficient (RC) of T1 as a measure of uncertainty was estimated in each ROI using the data pre-RT and at wk-3. The individual T1 changes at later time points were evaluated compared to the estimated RCs. Results: The 2-flip angle method produced small RCs in GM (9.7–11.7%) but large RCs in WM (12.2–13.6%) compared to the saturation-recovery (SR) method (11.0–17.7% for GM and 7.5–11.2% for WM). More than 81% of individual T1 changes were within T1 uncertainty ranges defined by RCs. Conclusion: Our study suggests that the impact of T1 uncertainty on physiological parameters derived from DCE MRI is not negligible. A short scan with 2 flip angles is able to achieve repeatability of T1 estimates similar to a long scan with 5 different TRs, and is desirable to be integrated in the DCE protocol. Present study was supported by National Institute of Health (NIH) under grant numbers; UO1 CA183848 and RO1 NS064973.

60 APPLIED LIFE SCIENCES↗

SU-D-204-05: Quantitative Comparison of a High Resolution Micro-Angiographic Fluoroscopic (MAF) Detector with a Standard Flat Panel Detector (FPD) Using the New Metric of Generalized Measured Relative Object Detectability (GM-ROD)

Purpose: In endovascular image-guided neuro-interventions, visualization of fine detail is paramount. For example, the ability of the interventionist to visualize the stent struts depends heavily on the x-ray imaging detector performance. Methods: A study to examine the relative performance of the high resolution MAF-CMOS (pixel size 75µm, Nyquist frequency 6.6 cycles/mm) and a standard Flat Panel Detector (pixel size 194µm, Nyquist frequency 2.5 cycles/mm) detectors in imaging a neuro stent was done using the Generalized Measured Relative Object Detectability (GM-ROD) metric. Low quantum noise images of a deployed stent were obtained by averaging 95 frames obtained by both detectors without changing other exposure or geometric parameters. The square of the Fourier transform of each image is taken and divided by the generalized normalized noise power spectrum to give an effective measured task-specific signal-to-noise ratio. This expression is then integrated from 0 to each of the detector’s Nyquist frequencies, and the GM-ROD value is determined by taking a ratio of the integrals for the MAF-CMOS to that of the FPD. The lower bound of integration can be varied to emphasize high frequencies in the detector comparisons. Results: The MAF-CMOS detector exhibits vastly superior performance over the FPD when integrating over all frequencies, yielding a GM-ROD value of 63.1. The lower bound of integration was stepped up in increments of 0.5 cycles/mm for higher frequency comparisons. As the lower bound increased, the GM-ROD value was augmented, reflecting the superior performance of the MAF-CMOS in the high frequency regime. Conclusion: GM-ROD is a versatile metric that can provide quantitative detector and task dependent comparisons that can be used as a basis for detector selection. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-E-E-07: An Adaptable Approach for Education On Medical Physics at Undergraduate and Postgraduate Levels

Purpose: To contribute to the professional profile of future medical physicists, technologists and physicians, and implement an adaptable educational strategy at both undergraduate and postgraduate levels. Methods: The Medical Physics Block of Electives (MPBE) designed was adapted to the Program of B.S. in Physics. The conferences and practical activities were developed with participatory methods, with interdisciplinary collaboration from research institutions and hospitals engaged on projects of Research, Development and Innovation (RDI). The scientific education was implemented by means of critical analysis of scientific papers and seminars where students debated on solutions for real research problems faced by medical physicists. This approach included courses for graduates not associated to educational programs of Medical Physics (MP). Results: The implementation of the MPBE began in September 2014, with the electives of Radiation MP and Introduction to Nuclear Magnetic Resonance. The students of second year received an Introduction to MP. This initiative was validated by the departmental Methodological Workshop, which promoted the full implementation of the MPBE. Both postgraduated and undergraduate trainees participated in practices with our DICOM viewer system, a local prototype for photoplethysmography and a home-made interface for ROC analysis, built with MATLAB. All these tools were designed and constructed in previous RDI projects. The collaborative supervision of University’s researchers with clinical medical physicists will allow to overcome the limitations of residency in hospitals, to reduce the workload for clinical supervisors and develop appropriate educational activities. Conclusion: We demonstrated the feasibility of adaptable educational strategies, considering available resources. This provides an innovative way for prospective medical physicists, technologists and radiation oncologists. This strategy can be implemented in several regions without formal programs of MP, like most of developing countries. Starting with undergraduate students would allow to reach appropriate certification faster than most of traditional or alternative approaches for education on MP. The authors acknowledge Radiation Consulting Group, LLC, an Arizona Corporation which promotes the use of ionizing radiation in the healing arts, for the “Oscar Luis Caballero” travel grant. The authors thanks to professors Meisbel Daudinot, David Adame and Alexander Pascau for the practices through imagis, imageROC and ANGIODIN PD3000 respectively.

60 APPLIED LIFE SCIENCES↗

SU-E-I-55: The Contribution to Skin Dose Due to Scatter From the Patient Table and the Head Holder During Fluoroscopy

Purpose: To determine contributions to skin dose due to scatter from the table and head holder used during fluoroscopy, and also to explore alternative design material to reduce the scatter dose. Methods: Measurements were made of the primary and scatter components of the xray beam exiting the patient table and a cylindrical head holder used on a Toshiba Infinix c-arm unit as a function of kVp for the various beam filters on the machine and for various field sizes. The primary component of the beam was measured in air with the object placed close to the x-ray tube with an air gap between it and a 6 cc parallel-plate ionization chamber and with the beam collimated to a size just larger than the chamber. The primary plus scatter radiation components were measured with the object moved to a position in the beam next to the chamber for larger field sizes. Both sets of measurements were preformed while keeping the source-to-chamber distance fixed. The scatter fraction was estimated by taking the ratio of the difference between the two measurements and the reading that included both primary and scatter. Similar measurements were also made for a 2.3 cm thick Styrofoam block which could substitute for the patient support. Results: The measured scatter fractions indicate that the patient table as well as the head holder contributes an additional 10–16% to the patient entrance dose depending on field size. Forward scatter was reduced with the Styrofoam block so that the scatter fraction was about 4–5%. Conclusion: The results of this investigation demonstrated that scatter from the table and head holder used in clinical fluoroscopy contribute substantially to the skin dose. The lower contribution of scatter from Styrofoam suggests that there is an opportunity to redesign patient support accessories to reduce the skin dose. Partial support from NIH grant R01EB002873 and Toshiba Medical Systems Corporation Equipment Grant.

60 APPLIED LIFE SCIENCES↗

SU-E-J-66: Significant Anatomical and Dosimetric Changes Observed with the Pharyngeal Constrictor During Head and Neck Radiotherapy Elicited From Daily Deformable Image Registration and Dose Accumulation

Purpose: To evaluate the anatomical changes and associated dosimetric consequences to the pharyngeal constrictor (PC) that occurs during head and neck radiotherapy (H&N RT). Methods: A cohort of 13 oro-pharyngeal cancer patients, who had daily CBCT’s for localization, was retrospectively studied. On every 5th CBCT, PC was manually delineated by a radiation oncologist. The anterior-posterior PC thickness was measured at the C3 level. Delivered dose to PC was estimated by calculating daily doses on CBCT’s, and accumulating to corresponding planning CT images. For accumulation, a parameter-optimized B- spline-based deformable image registration algorithm (Elastix) was used, in conjunction with an energy-mass mapping dose transfer algorithm. Mean and maximum dose (Dmean, Dmax) to PC was determined and compared with corresponding planned quantities. Results: The mean (±standard deviation) volume increase (ΔV) and thickness increase (Δt) over the course of 35 total fractions were 54±33% (11.9±7.6 cc), and 63±39% (2.9±1.9 mm), respectively. The resultant cumulative mean dose increase from planned dose to PC (ΔDmean) was 1.4±1.3% (0.9±0.8 Gy), while the maximum dose increase (ΔDmax) was 0.0±1.6% (0.0±1.1 Gy). Patients with adaptive replanning (n=6) showed a smaller mean dose increase than those without (n=7); 0.5±0.2% (0.3±0.1 Gy) vs. 2.2±1.4% (1.4±0.9 Gy). There was a statistically significant (p<0.0001) strong correlation between ΔDmean and Δt (Pearson coefficient r=0.78), and a moderate-to-strong correlation (r=0.52) between ΔDmean and ΔV. Correlation between ΔDmean and weight loss ΔW (r=0.1), as well as ΔV and ΔW (r=0.2) were negligible. Conclusion: Patients were found to undergo considerable anatomical changes to pharyngeal constrictor during H&N RT, resulting in non-negligible dose deviations from intended dose. Results are indicative that pharyngeal constrictor thickness, measured at C3 level, is a good predictor for the dose change to the organ. Daily deformable registration and dose accumulation provide a reliable means to assess important anatomical and dosimetric changes to pharyngeal constrictor occurring during treatment. This work was supported in part by a research grant from Varian Medical Systems, Palo Alto, CA.

60 APPLIED LIFE SCIENCES↗

SU-E-J-73: Extension of a Clinical OIS/EMR/R&V System to Deliver Safe and Efficient Adaptive Plan-Of-The-Day Treatments Using a Fully Customizable Plan-Library-Based Workflow

Purpose: To extend a clinical Record and Verify (R&V) system to enable a safe and fast workflow for Plan-of-the-Day (PotD) adaptive treatments based on patient-specific plan libraries. Methods: Plan libraries for PotD adaptive treatments contain for each patient several pre-treatment generated treatment plans. They may be generated for various patient anatomies or CTV-PTV margins. For each fraction, a Cone Beam CT scan is acquired to support the selection of the plan that best fits the patient’s anatomy-of-the-day. To date, there are no commercial R&V systems that support PotD delivery strategies. Consequently, the clinical workflow requires many manual interventions. Moreover, multiple scheduled plans have a high risk of excessive dose delivery. In this work we extended a commercial R&V system (MOSAIQ) to support PotD workflows using IQ-scripting. The PotD workflow was designed after extensive risk analysis of the manual procedure, and all identified risks were incorporated as logical checks. Results: All manual PotD activities were automated. The workflow first identifies if the patient is scheduled for PotD, then performs safety checks, and continues to treatment plan selection only if no issues were found. The user selects the plan to deliver from a list of candidate plans. After plan selection, the workflow makes the treatment fields of the selected plan available for delivery by adding them to the treatment calendar. Finally, control is returned to the R&V system to commence treatment. Additional logic was added to incorporate off-line changes such as updating the plan library. After extensive testing including treatment fraction interrupts and plan-library updates during the treatment course, the workflow is running successfully in a clinical pilot, in which 35 patients have been treated since October 2014. Conclusion: We have extended a commercial R&V system for improved safety and efficiency in library-based adaptive strategies enabling a wide-spread implementation of those strategies. This work was in part funded by a research grant of Elekta AB, Stockholm, Sweden.

60 APPLIED LIFE SCIENCES↗

MO-AB-210-00: Diagnostic Ultrasound Imaging Quality Control and High Intensity Focused Ultrasound Therapy Hands-On Workshop

The goal of this ultrasound hands-on workshop is to demonstrate advancements in high intensity focused ultrasound (HIFU) and to demonstrate quality control (QC) testing in diagnostic ultrasound. HIFU is a therapeutic modality that uses ultrasound waves as carriers of energy. HIFU is used to focus a beam of ultrasound energy into a small volume at specific target locations within the body. The focused beam causes localized high temperatures and produces a well-defined regions of necrosis. This completely non-invasive technology has great potential for tumor ablation and targeted drug delivery. At the workshop, attendees will see configurations, applications, and hands-on demonstrations with on-site instructors at separate stations. The involvement of medical physicists in diagnostic ultrasound imaging service is increasing due to QC and accreditation requirements. At the workshop, an array of ultrasound testing phantoms and ultrasound scanners will be provided for attendees to learn diagnostic ultrasound QC in a hands-on environment with live demonstrations of the techniques. Target audience: Medical physicists and other medical professionals in diagnostic imaging and radiation oncology with interest in high-intensity focused ultrasound and in diagnostic ultrasound QC. Learning Objectives: Learn ultrasound physics and safety for HIFU applications through live demonstrations Get an overview of the state-of-the art in HIFU technologies and equipment Gain familiarity with common elements of a quality control program for diagnostic ultrasound imaging Identify QC tools available for testing diagnostic ultrasound systems and learn how to use these tools List of supporting vendors for HIFU and diagnostic ultrasound QC hands-on workshop: Philips Healthcare Alpinion Medical Systems Verasonics, Inc Zonare Medical Systems, Inc Computerized Imaging Reference Systems (CIRS), Inc. GAMMEX, Inc., Cablon Medical BV Steffen Sammet: NIH/NCI grant 5R25CA132822, NIH/NINDS grant 5R25NS080949 and Philips Healthcare research grant C32.

60 APPLIED LIFE SCIENCES↗

MO-AB-210-01: Ultrasound Imaging and Therapy-Hands On Workshop

The goal of this ultrasound hands-on workshop is to demonstrate advancements in high intensity focused ultrasound (HIFU) and to demonstrate quality control (QC) testing in diagnostic ultrasound. HIFU is a therapeutic modality that uses ultrasound waves as carriers of energy. HIFU is used to focus a beam of ultrasound energy into a small volume at specific target locations within the body. The focused beam causes localized high temperatures and produces a well-defined regions of necrosis. This completely non-invasive technology has great potential for tumor ablation and targeted drug delivery. At the workshop, attendees will see configurations, applications, and hands-on demonstrations with on-site instructors at separate stations. The involvement of medical physicists in diagnostic ultrasound imaging service is increasing due to QC and accreditation requirements. At the workshop, an array of ultrasound testing phantoms and ultrasound scanners will be provided for attendees to learn diagnostic ultrasound QC in a hands-on environment with live demonstrations of the techniques. Target audience: Medical physicists and other medical professionals in diagnostic imaging and radiation oncology with interest in high-intensity focused ultrasound and in diagnostic ultrasound QC. Learning Objectives: Learn ultrasound physics and safety for HIFU applications through live demonstrations Get an overview of the state-of-the art in HIFU technologies and equipment Gain familiarity with common elements of a quality control program for diagnostic ultrasound imaging Identify QC tools available for testing diagnostic ultrasound systems and learn how to use these tools List of supporting vendors for HIFU and diagnostic ultrasound QC hands-on workshop: Philips Healthcare Alpinion Medical Systems Verasonics, Inc Zonare Medical Systems, Inc Computerized Imaging Reference Systems (CIRS), Inc. GAMMEX, Inc., Cablon Medical BV Steffen Sammet: NIH/NCI grant 5R25CA132822, NIH/NINDS grant 5R25NS080949 and Philips Healthcare research grant C32.

60 APPLIED LIFE SCIENCES↗

MO-AB-210-02: Ultrasound Imaging and Therapy-Hands On Workshop

The goal of this ultrasound hands-on workshop is to demonstrate advancements in high intensity focused ultrasound (HIFU) and to demonstrate quality control (QC) testing in diagnostic ultrasound. HIFU is a therapeutic modality that uses ultrasound waves as carriers of energy. HIFU is used to focus a beam of ultrasound energy into a small volume at specific target locations within the body. The focused beam causes localized high temperatures and produces a well-defined regions of necrosis. This completely non-invasive technology has great potential for tumor ablation and targeted drug delivery. At the workshop, attendees will see configurations, applications, and hands-on demonstrations with on-site instructors at separate stations. The involvement of medical physicists in diagnostic ultrasound imaging service is increasing due to QC and accreditation requirements. At the workshop, an array of ultrasound testing phantoms and ultrasound scanners will be provided for attendees to learn diagnostic ultrasound QC in a hands-on environment with live demonstrations of the techniques. Target audience: Medical physicists and other medical professionals in diagnostic imaging and radiation oncology with interest in high-intensity focused ultrasound and in diagnostic ultrasound QC. Learning Objectives: Learn ultrasound physics and safety for HIFU applications through live demonstrations Get an overview of the state-of-the art in HIFU technologies and equipment Gain familiarity with common elements of a quality control program for diagnostic ultrasound imaging Identify QC tools available for testing diagnostic ultrasound systems and learn how to use these tools List of supporting vendors for HIFU and diagnostic ultrasound QC hands-on workshop: Philips Healthcare Alpinion Medical Systems Verasonics, Inc Zonare Medical Systems, Inc Computerized Imaging Reference Systems (CIRS), Inc. GAMMEX, Inc., Cablon Medical BV Steffen Sammet: NIH/NCI grant 5R25CA132822, NIH/NINDS grant 5R25NS080949 and Philips Healthcare research grant C32.

60 APPLIED LIFE SCIENCES↗

MO-D-213-06: Quantitative Image Quality Metrics Are for Physicists, Not Radiologists: How to Communicate to Your Radiologists Using Their Language

Purpose: A framework for explaining differences in image quality to non-technical audiences in medial imaging is needed. Currently, this task is something that is learned “on the job.” The lack of a formal methodology for communicating optimal acquisition parameters into the clinic effectively mitigates many technological advances. As a community, medical physicists need to be held responsible for not only advancing image science, but also for ensuring its proper use in the clinic. This work outlines a framework that bridges the gap between the results from quantitative image quality metrics like detectability, MTF, and NPS and their effect on specific anatomical structures present in diagnostic imaging tasks. Methods: Specific structures of clinical importance were identified for a body, an extremity, a chest, and a temporal bone protocol. Using these structures, quantitative metrics were used to identify the parameter space that should yield optimal image quality constrained within the confines of clinical logistics and dose considerations. The reading room workflow for presenting the proposed changes for imaging each of these structures is presented. The workflow consists of displaying images for physician review consisting of different combinations of acquisition parameters guided by quantitative metrics. Examples of using detectability index, MTF, NPS, noise and noise non-uniformity are provided. During review, the physician was forced to judge the image quality solely on those features they need for diagnosis, not on the overall “look” of the image. Results: We found that in many cases, use of this framework settled mis-agreements between physicians. Once forced to judge images on the ability to detect specific structures inter reader agreement was obtained. Conclusion: This framework will provide consulting, research/industrial, or in-house physicists with clinically relevant imaging tasks to guide reading room image review. This framework avoids use of the overall “look” or “feel” to dictate acquisition parameter selection. Equipment grants GE Healthcare.

60 APPLIED LIFE SCIENCES↗

MO-FG-213-04: Managing the Relationship

Academic-industrial collaborations are playing an increasingly prominent role in medical physics research. Successful partnerships have enabled truly translational, benchtop-to-bedside research that has significantly and positively impacted our field. Given the current flat or depleting trends in federal funding, and the increasing emphasis in the medical physics community on demonstrating translatability, efficacy, and safety prior to widespread clinical use, it is anticipated that such partnerships will become ever more important in advancing our field. In the future, it is likely that neither academia alone, nor industry alone, will be able to bring significant innovation to successfully impact patient care in radiotherapy. Such innovation will require partnership and symbiosis through the lifetime of the project. This symposium is aimed at professionals from academia and the industry who are interested in either initiating new collaborations or maintaining and improving existing partnerships. We will hear from four thought leaders from industry and academia on critical aspects of building and maintaining successful academic-industrial research partnerships. The following topics will be addressed: 1. Motivations: The industry perspective [Kevin Brown, Elekta] What goes into the development of a company’s R&D roadmap What are the motivations and expectations of the industry from academic partners How can academics make a successful pitch by identifying projects aligned with a company’s roadmap Why are some relationships successful and some not Milestones and progress reports - Why do we need them 2. Motivations: The academic perspective [T. Rock Mackie, Univ. of Madison, WI; Tomotherapy] What are the motivations and expectations of academic partners from the industry What are the cultural differences in academia vs industry on sharing information, exchanging ideas Partnership or entrepreneurship? When does each option make sense 3. Industrial Grants and Research Contracts – a Primer [Norbert Pelc; Stanford University] What topics are suited to industrial grants vs. academic grants How do resources (personnel effort, tuition) get allocated and charged in academia What are reasonable resource and timeline requests for small and big projects; from small and big companies “Fair market value” considerations Sections of a research agreement (IP including software confidential information, publications, data, exclusivity, support) 4. Managing the relationship [John Wong, Johns Hopkins University] How to effectively collaborate with each other How to adapt to changes in the relationship How to renew funding with the industry Moderated Panel Discussion [All speakers + moderators] Learning Objectives: 1. Understand the motivations of each partner 2. Elements that contribute to a successful partnership 3. Avoiding pitfalls - Challenges on either side that may derail a project 4. How to frame a research grant and agreement 5. How to sustain the collaborative relationship Amit Sawant: Funding from: NIH. Varian, Elekta and VisionRT; Michelle Svatos: Employee and shareholder: Varian, Board Member, TopasMC; Kevin Brown: Employee, Elekta; T. Rock Mackie: Consultant, Accuray; Norbert Pelc: Research support: Philips Healthcare, GE Healthcare; John Wong: Funding from NIH, Xstrahl and Elekta. Co-founder and advisor for JPLC Associates, LLC.

07 ISOTOPE AND RADIATION SOURCES↗

SU-C-201-03: Ionization Chamber Collection Efficiency in Pulsed Radiation Fields of High Pulse Dose

Purpose: To investigate the reduction of collection efficiency of ionization chambers (IC) by volume recombination and its correction in pulsed fields of very high pulse dose. Methods: Measurements of the collection efficiency of a plane-parallel advanced Markus IC (PTW 34045, 1mm electrode spacing, 300V nominal voltage) were obtained for collection voltages of 100V and 300V by irradiation with a pulsed electron beam (20MeV) of varied pulse dose up to approximately 600mGy (0.8nC liberated charge). A reference measurement was performed with a Faraday cup behind the chamber. It was calibrated for the liberated charge in the IC by a linear fit of IC measurement to reference measurement at low pulse doses. The results were compared to the commonly used two voltage approximation (TVA) and to established theories for volume recombination, with and without considering a fraction of free electrons. In addition, an equation system describing the charge transport and reactions in the chamber was solved numerically. Results: At 100V collection voltage and moderate pulse doses the established theories accurately predict the observed collection efficiency, but at extreme pulse doses a fraction of free electrons needs to be considered. At 300V the observed collection efficiency deviates distinctly from that predicted by any of the established theories, even at low pulse doses. However, the numeric solution of the equation system is able to reproduce the measured collection efficiency across the entire dose range of both voltages with a single set of parameters. Conclusion: At high electric fields (3000V/cm here) the existing theoretical descriptions of collection efficiency, including the TVA, are inadequate to predict pulse dose dependency. Even at low pulse doses they might underestimate collection efficiency. The presented, more accurate numeric solution, which considers additional effects like electric shielding by the charges, might provide a valuable tool for future investigations. This project was funded by the German ministry of research and education (BMBF) under grant number: 03Z1N511 and by the state of Saxony under grant number: B 209.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-D-206-02: Evaluation of Partial Storage of the System Matrix for Cone Beam Computed Tomography Using a GPU Platform

Purpose: Iterative reconstruction algorithms in computed tomography (CT) require a fast method for computing the intersections between the photons’ trajectories and the object, also called ray-tracing or system matrix computation. This work evaluates different ways to store the system matrix, aiming to reconstruct dense image grids in reasonable time. Methods: We propose an optimized implementation of the Siddon’s algorithm using graphics processing units (GPUs) with a novel data storage scheme. The algorithm computes a part of the system matrix on demand, typically, for one projection angle. The proposed method was enhanced with accelerating options: storage of larger subsets of the system matrix, systematic reuse of data via geometric symmetries, an arithmetic-rich parallel code and code configuration via machine learning. It was tested on geometries mimicking a cone beam CT acquisition of a human head. To realistically assess the execution time, the ray-tracing routines were integrated into a regularized Poisson-based reconstruction algorithm. The proposed scheme was also compared to a different approach, where the system matrix is fully pre-computed and loaded at reconstruction time. Results: Fast ray-tracing of realistic acquisition geometries, which often lack spatial symmetry properties, was enabled via the proposed method. Ray-tracing interleaved with projection and backprojection operations required significant additional time. In most cases, ray-tracing was shown to use about 66 % of the total reconstruction time. In absolute terms, tracing times varied from 3.6 s to 7.5 min, depending on the problem size. The presence of geometrical symmetries allowed for non-negligible ray-tracing and reconstruction time reduction. Arithmetic-rich parallel code and machine learning permitted a modest reconstruction time reduction, in the order of 1 %. Conclusion: Partial system matrix storage permitted the reconstruction of higher 3D image grid sizes and larger projection datasets at the cost of additional time, when compared to the fully pre-computed approach. This work was supported in part by the Fonds de recherche du Quebec - Nature et technologies (FRQ-NT). The authors acknowledge partial support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council of Canada (Grant No. 432290).

60 APPLIED LIFE SCIENCES↗

SU-F-E-07: Web-Based Training for Radiosurgery: Methods and Metrics for Global Reach

Purpose: Webinars have become an evolving tool with greater or lesser success in reaching health care providers (HCPs). This study seeks to assess best practices and metrics for success in webinar deployment for optimal global reach. Methods: Webinars have been developed and launched to reach practicing health care providers in the field of radiation oncology and radiosurgery. One such webinar was launched in early February 2016. “Multiple Brain Metastases & Volumetric Modulated Arc Radiosurgery: Refining the Single-Isocenter Technique to Benefit Surgeons and Patients” presented by Drs. Fiveash and Thomas from UAB was submitted to and accredited by the Institute for Medical Education as qualifying for CME as well as MDCB for educational credit for dosimetrists, in order to encourage participation. MedicalPhysicsWeb was chosen as the platform to inform attendees regarding the webinar. Further IME accredited the activity for 1 AMA PRA Category 1 credit for physicians & medical physicists. The program was qualified by the ABR in meeting the criteria for self-assessment towards fulfilling MOC requirements. Free SAMs credits were underwritten by an educational grant from Varian Medical Systems. Results: The webinar in question attracted 992 pre-registrants from 66 countries. Outside the US and Canada; 11 were from the Americas; 32 were from Europe; 9 from the Middle East and Africa. Australasia and the Indian subcontinent represented the remaining 14 countries. Pre-registrants included 423 Medical Physicists, 225 Medical Dosimetrists, 24 Radiation Therapists, 66 Radiation Oncologists & other. Conclusion: The effectiveness of CME and SAM-CME programs such as this can be gauged by the high rate of respondents who state an intention to change practice habits, a primary goal of continuing medical education and self-assessment. This webinar succeeded in being the most successful webinar on Medical Physics Web as measured by pre-registration, participation and participation to pre-registration ratio. R.A. Schulz is an employee of Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

SU-F-P-20: Predicting Waiting Times in Radiation Oncology Using Machine Learning

Purpose: Waiting times remain one of the most vexing patient satisfaction challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick or in pain, to worry about when they will receive the care they need. These waiting periods are often difficult for staff to predict and only rough estimates are typically provided based on personal experience. This level of uncertainty leaves most patients unable to plan their calendar, making the waiting experience uncomfortable, even painful. In the present era of electronic health records (EHRs), waiting times need not be so uncertain. Extensive EHRs provide unprecedented amounts of data that can statistically cluster towards representative values when appropriate patient cohorts are selected. Predictive modelling, such as machine learning, is a powerful approach that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The application of a machine learning algorithm to waiting time data has the potential to produce personalized waiting time predictions such that the uncertainty may be removed from the patient’s waiting experience. Methods: In radiation oncology, patients typically experience several types of waiting (eg waiting at home for treatment planning, waiting in the waiting room for oncologist appointments and daily waiting in the waiting room for radiotherapy treatments). A daily treatment wait time model is discussed in this report. To develop a prediction model using our large dataset (with more than 100k sample points) a variety of machine learning algorithms from the Python package sklearn were tested. Results: We found that the Random Forest Regressor model provides the best predictions for daily radiotherapy treatment waiting times. Using this model, we achieved a median residual (actual value minus predicted value) of 0.25 minutes and a standard deviation residual of 6.5 minutes. This means that the majority of our estimates are within 6.5 minutes of the actual wait time. Conclusion: The goal of this project was to define an appropriate machine learning algorithm to estimate waiting times based on the collective knowledge and experience learned from previous patients. Our results offer an opportunity to improve the information that is provided to patients and family members regarding the amount of time they can expect to wait for radiotherapy treatment at our centre. AJ acknowledges support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290) and from the 2014 Q+ Initiative of the McGill University Health Centre.

60 APPLIED LIFE SCIENCES↗

SU-F-P-33: Combining Research and Professional Practice in the Clinical Setting: A Medical Physicist Personal Experience

Purpose: To initiate a discussion on the current and evolving role of Medical Physicists based on author’s professional and research experience in patient safety and quality control. Methods: Several professionals of the departments of Medical Physics and Radiation Oncology, chiefly devoted to clinical tasks, began a research program on patient safety and quality control in a framework provided by the implementation of intraoperative radiotherapy (IORT). We performed studies on virtual simulation for IORT, in vivo dosimetry, failure mode and effect analysis (FMEA), statistical process control (SPC), and receiver operating characteristics of dosimetric equipment. This was done with the support of our research foundation and different grants while continuing with our departmental clinical routine involving about 1600 annual treatments with two linacs and different brachytherapy techniques. Results: We published 5 papers in international journals in the last two years. This author conducted a doctoral research which resulted in a dissertation in 2015. The extra time spent after treatments was essential to succeed. Funding and support achieved via our foundation played a crucial role; but this would have not been possible without punctual external mentoring and partnership. FMEA conclusions were able to be implemented only with staff commitment; however, conclusions concerning equipment cannot be easily communicated to manufacturers. These tasks required extra training in the appropriated methods. Conclusion: Research needed the support of a dedicated foundation, which would have been very difficult to obtain with the sole participation of our departments. FMEA and SPC results may need engagement of staff and manufacturers, respectively, hard to achieve without strong recommendations or even a regulatory framework. All these fields need evolution of Medical Physicists’ roles and additional training. Devotion to both clinical tasks and research could be unfeasible for Medical Physicists in the clinical setting without the appropriate rearrangement of their schedules and tasks. Supported by grants IPT-300000-2010-3 and PI11/01659. ERDF funds and Spanish Government.

60 APPLIED LIFE SCIENCES↗

SU-F-P-35: A Multi-Institutional Plan Quality Checking Tool Built On Oncospace: A Shared Radiation Oncology Database System

Purpose: Late toxicity from radiation to critical structures limits the possible dose in Radiation Therapy. Perfectly conformal treatment of a target is not realizable, so the clinician must accept a certain level of collateral radiation to nearby OARs. But how much? General guidelines exist for healthy tissue sparing which guide RT treatment planning, but are these guidelines good enough to create the optimal plan given the individualized patient anatomy? We propose a means to evaluate the planned dose level to an OAR using a multi-institutional data-store of previously treated patients, so a clinician might reconsider planning objectives. Methods: The tool is built on Oncospace, a federated data-store system, which consists of planning data import, web based analysis tools, and a database containing:1) DVHs: dose by percent volume delivered to each ROI for each patient previously treated and included in the database.2) Overlap Volume Histograms (OVHs): Anatomical measure defined as the percent volume of an ROI within a given distance to target structures.Clinicians know what OARs are important to spare. For any ROI, Oncospace knows for which patients’ anatomy that ROI was harder to plan in the past (the OVH is less). The planned dose should be close to the least dose of previous patients. The tool displays the dose those OARs were subjected to, and the clinician can make a determination about the planning objectives used.Multiple institutions contribute to the Oncospace Consortium, and their DVH and OVH data are combined and color coded in the output. Results: The Oncospace website provides a plan quality display tool which identifies harder to treat patients, and graphically displays the dose delivered to them for comparison with the proposed plan. Conclusion: The Oncospace Consortium manages a data-store of previously treated patients which can be used for quality checking new plans. Grant funding by Elekta.

60 APPLIED LIFE SCIENCES↗